Early Stopping feature

[neo133]

Hi,
Thanks for the great repo.
I wanted to ask if there's any feature available to earlystop the training based on monitoring any particular metric?
Please help how to add that in the config.
I am trying to fine-tune PPOCRv4 on my dataset by i couldn't find any implementation of early stopping in the base code of the repo. Please direct me to the particular code where it is implemented.

[GreatV]

Currently, PaddleOCR does not have a built-in Early Stopping feature in the base code, including for PPOCRv4. The official documentation and discussions do not indicate any direct implementation for early stopping, such as monitoring metrics (e.g., validation loss or accuracy) to halt training automatically when improvements plateau.

How to Add Early Stopping:

To implement early stopping, you would need to modify the training loop manually. Here’s a general outline of how you can do it:

1. Modify the training script:
   Locate the main training script (typically, this might be tools/train.py or similar in PaddleOCR).

2. Monitor a metric:
   During training, after every validation epoch, calculate the metric you want to monitor (e.g., validation loss or accuracy).

3. Early Stopping Logic:
   Keep track of the best metric value so far. If for a set number of epochs (patience) the metric doesn’t improve, stop the training.

4. Example code snippet:

   best_metric = None
   patience = 5
   wait = 0
   
   for epoch in range(num_epochs):
       # Training code
       # ...
   
       # Validation code
       metric_value = evaluate(...)  # your validation metric
   
       if best_metric is None or metric_value > best_metric:
           best_metric = metric_value
           wait = 0
           # Optionally save the best model here
       else:
           wait += 1
   
       if wait >= patience:
           print(f"Early stopping at epoch {epoch}")
           break

Config File:
Currently, you cannot add early stopping directly in the YAML config files for PaddleOCR. This is a feature you’ll need to code into the training script itself. There is no parameter like early_stopping in the provided configurations.

Reference:
No relevant issues or discussions directly address the implementation of early stopping. Optimization and fine-tuning discussions (like this one) focus on other forms of model optimization and do not mention early stopping.

Summary:

• No built-in early stopping in PaddleOCR or PPOCRv4.
• Requires manual modification of training script.
• Not configurable via YAML config.
• No direct references in issues or discussions.

If you need more guidance or a specific implementation example for PPOCRv4, let me know your exact training setup, and I can help with a more tailored code snippet.

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Response generated by 🤖 feifei-bot | gpt-4.1

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